Method and apparatus for fine tuning and optimizing nvme-of ssds

ABSTRACT

A data storage system includes: a plurality of data storage devices; a motherboard containing a baseboard management controller (BMC); and a network switch configured to route network traffic to the plurality of data storage devices. The BMC is configured to identify a group of data storage devices among the plurality of data storage devices based on device-specific information received from the plurality of data storage devices and send identifiers of the group of data storage devices to a querying party.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application is a continuation application of U.S. patentapplication Ser. No. 16/384,508 filed Apr. 15, 2019, which is acontinuation application of U.S. patent application Ser. No. 15/674,690filed Aug. 11, 2017 (now issued to U.S. Pat. No. 10,310,745), whichclaims the benefits of and priority to U.S. Provisional PatentApplication Ser. No. 62/508,811 filed May 19, 2017, the disclosures ofwhich are incorporated herein by reference in their entirety.

TECHNICAL FIELD

The present disclosure relates generally to storage devices, moreparticularly, to a system and method for fine tuning and optimizingNVMe-oF solid-state drives (SSDs).

BACKGROUND

Non-volatile memory (NVM) express over Fabrics (NVMe-oF) is a newindustry standard defining a common architecture that supports an NVMeblock storage protocol over a wide range of storage networking fabricssuch as Ethernet, Fibre Channel, InfiniB and, and a transmission controlprotocol (TCP) network. The data storage devices compatible with NVMe-oFstandard, herein also referred to as NVMe-oF devices, have similar formfactors as standard solid-state drives (SSDs) and hard disk drives(HDDs), for example, 2.5″ and 3.5″ disk drives. NVMe-oF devices arecommonly used in an enterprise environment or in a datacenter. However,the NVMe-oF specification does not address optimization of an NVMe-oFdevice for specific applications, for example, machine learning and datamining applications. Customers may use NVMe-oF devices that aremanufactured by different vendors having different data profiles.

Cloud computing is becoming popular among enterprise users. Instead ofowning computing resources, companies prefer to lease computingresources from cloud service providers such as Amazon Web Services®(AWS), Microsoft Azure® services, and Google Cloud Platform®. Thestorage devices used in a datacenter will have a large amount of datathat are frequently replaced based on the tenancy applications and theiroperating configurations can change as tenancy changes. In addition,those cloud storage devices are not typically optimized for leasing andsubscription models. Hence, it is desirable to optimize fresh orpre-assigned storage devices in a datacenter prior to assigningapplications and writing data to them.

SUMMARY

According to one embodiment, a data storage system includes: a pluralityof data storage devices; a motherboard containing a baseboard managementcontroller (BMC); and a network switch configured to route networktraffic to the plurality of data storage devices. The BMC is configuredto identify a group of data storage devices among the plurality of datastorage devices based on device-specific information received from theplurality of data storage devices and send identifiers of the group ofdata storage devices to a querying party.

According to another embodiment, a method includes: receivingdevice-specific information from a plurality of data storage devicesincluded in a data storage system using a baseboard managementcontroller (BMC); identifying a group of data storage devices among theplurality of data storage devices based on attributes of the pluralityof data storage devices; and sending identifiers of the group of datastorage devices to a querying party.

The above and other preferred features, including various novel detailsof implementation and combination of events, will now be moreparticularly described with reference to the accompanying figures andpointed out in the claims. It will be understood that the particularsystems and methods described herein are shown by way of illustrationonly and not as limitations. As will be understood by those skilled inthe art, the principles and features described herein may be employed invarious and numerous embodiments without departing from the scope of thepresent disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are included as part of the presentspecification, illustrate the presently preferred embodiment andtogether with the general description given above and the detaileddescription of the preferred embodiment given below serve to explain andteach the principles described herein.

FIG. 1 shows an example data storage system, according to oneembodiment;

FIGS. 2A, 2B, 2C, and 2D show an example flowchart for specifying andoptimizing SSDs present in a chassis using a BMC, according to oneembodiment; and

FIG. 3 shows example transactions between a BMC and an SSD, according toone embodiment.

The figures are not necessarily drawn to scale, and elements of similarstructures or functions are generally represented by like referencenumerals for illustrative purposes throughout the figures. The figuresare only intended to facilitate the description of the variousembodiments described herein. The figures do not describe every aspectof the teachings disclosed herein and do not limit the scope of theclaims.

DETAILED DESCRIPTION

Each of the features and teachings disclosed herein can be utilizedseparately or in conjunction with other features and teachings toprovide a system and method for fine tuning and optimizing solid-statedrives (SSDs) that are compatible with the NVMe-oF standard.Representative examples utilizing many of these additional features andteachings, both separately and in combination, are described in furtherdetail with reference to the attached figures. This detailed descriptionis merely intended to teach a person of skill in the art further detailsfor practicing aspects of the present teachings and is not intended tolimit the scope of the claims. Therefore, combinations of featuresdisclosed above in the detailed description may not be necessary topractice the teachings in the broadest sense, and are instead taughtmerely to describe particularly representative examples of the presentteachings.

In the description below, for purposes of explanation only, specificnomenclature is set forth to provide a thorough understanding of thepresent disclosure. However, it will be apparent to one skilled in theart that these specific details are not required to practice theteachings of the present disclosure.

Some portions of the detailed descriptions herein are presented in termsof algorithms and symbolic representations of operations on data bitswithin a computer memory. These algorithmic descriptions andrepresentations are used by those skilled in the data processing arts toeffectively convey the substance of their work to others skilled in theart. An algorithm is here, and generally, conceived to be aself-consistent sequence of steps leading to a desired result. The stepsare those requiring physical manipulations of physical quantities.Usually, though not necessarily, these quantities take the form ofelectrical or magnetic signals capable of being stored, transferred,combined, compared, and otherwise manipulated. It has proven convenientat times, principally for reasons of common usage, to refer to thesesignals as bits, values, elements, symbols, characters, terms, numbers,or the like.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise as apparent from the below discussion, itis appreciated that throughout the description, discussions utilizingterms such as “processing,” “computing,” “calculating,” “determining,”“displaying,” or the like, refer to the action and processes of acomputer system, or similar electronic computing device, thatmanipulates and transforms data represented as physical (electronic)quantities within the computer system's registers and memories intoother data similarly represented as physical quantities within thecomputer system memories or registers or other such information storage,transmission or display devices.

Moreover, the various features of the representative examples and thedependent claims may be combined in ways that are not specifically andexplicitly enumerated in order to provide additional useful embodimentsof the present teachings. It is also expressly noted that all valueranges or indications of groups of entities disclose every possibleintermediate value or intermediate entity for the purpose of an originaldisclosure, as well as for the purpose of restricting the claimedsubject matter. It is also expressly noted that the dimensions and theshapes of the components shown in the figures are designed to help tounderstand how the present teachings are practiced, but not intended tolimit the dimensions and the shapes shown in the examples.

The present disclosure describes a data storage system and a method forfine tuning and optimizing data storage devices present in the datastorage system. The data storage devices may be of various types andsizes made and distributed by different manufacturers and vendors.According to one embodiment, the data storage device is a solid-statedrive (SSD) that is compatible with the NVMe-oF specification, hereinalso referred to as an NVMe-oF device or an NVMe-oF SSD. The NVMe-oFdevice is compatible with various underlying storage networking fabricssuch as Ethernet, Fibre Channel, InfiniBand, and a transmission controlprotocol (TCP) network. According to one embodiment, the present datastorage system is a rack-mounted system. Each rack in a datacenter cancontain a combination of sleds and/or trays for accommodating computeand data storage devices.

The present data storage system includes a chassis and a motherboardcontaining a baseboard management controller (BMC) disposed in thechassis. According to one embodiment, the BMC can optimize NVMe-oF SSDspresent in the chassis of the data storage system. After the datastorage system is initialized, the BMC is aware of all NVMe-oF SSDspresent in the chassis. The NVMe-oF SSDs that are identified by the BMCas having desired attributes can be optimized and assigned to a specificapplication.

The present data storage system allows a user or an application to takeadvantage of the BMC's knowledge on the SSDs that are present in thechassis when making determination to use the SSDs that satisfyuser/application-specific requirements. The BMC can identify SSDs thatcan meet the data profiles and attributes of a service level agreement(SLA) as specified by the use or the application before committing andassigning the SSDS according to the SLA. The BMC can prepare theselected SSDs, for example securely erasing the stored data, after thecurrent-running service expires or before the new service launches.

The use of the BMC for identifying SSDs present in the chassis that meetthe required criteria and preparing them can lessen the burden of alocal CPU of the chassis allowing the local CPU to execute criticaland/or frequent tasks such as data input and output (I/O) withoutsacrificing the performance. The BMC can handle less critical and/orinfrequent tasks such as the identification of the SSDs present in thechassis, updating the data profiles of the SSDs, preparing the SSDs fora new service or application. The total cost of ownership (TCO) of thedata storage system including capital expenditure (CapEx) and/oroperating expenditure (Opex) can be lowered by properly delegatingless-critical and infrequent tasks to the BMC that are otherwiseexecuted by the local CPU. For example, the local CPU in the chassis maybe replaced with a less expensive CPU that has a specification enough toperform the critical and/or frequent tasks equivalent to the originalCPU. This can result in no or minimal impact to the I/O performance ofthe data storage system while reducing the cost.

FIG. 1 shows an example data storage system, according to oneembodiment. The data storage system 100 can be one of many of datastorage systems in a data center of a cloud service provider. Examplesof the cloud service provider include Amazon Web Services (AWS),Microsoft Azure services, and Google Cloud Platform. The data centeralso has one or more computing nodes running applications 110 a, 110 b,and 110 c and a server 150 that provides an interface for the cloudservice.

The data storage system 100 has a chassis that can hold a plurality ofSSDs 130 a-130 e via a plurality of device ports of the chassis. Forexample, each SSD 130 can be inserted into a device port of the chassisusing a U.2 connector or other standard connectors. Although the presentexample shows three applications and five SSDs, but it is understoodthat any number of applications may run, and any number of SSDs may bepresent in the chassis. For example, up to 24 or 48 SSDs may be insertedto the device ports of the data storage system 100 depending on theconfiguration. The application 110 a may use data stored in the SSDs 130a and 130 c, the application 110 b may use data stored in the SSDs 130 band 130 d, and the application 110 c may use data stored in the SSD 130e. A user (e.g., an enterprise user) can run an application run over thecloud using the SSDs owned and managed by the cloud service provider.

The chassis includes a CPU 120, a BMC 121, a network switch 122configured to transport network signals, a peripheral componentinterconnect express (PCIe) switch 123 configured to transport PCIesignals over a PCIe bus, a plurality of uplink ports 125, and aplurality of downlink ports 126. According to one embodiment, theunderlying fabrics of the data storage system 110 is Ethernet. In thiscase, the network switch 122 is an Ethernet switch, and the uplink ports125 and the downlink ports 126 are Ethernet ports. Each of the downlinkports 126 is connected to a respective SSD 130.

The CPU 120 is configured to run an operating system (e.g., Linux) withsoftware-defined networking protocols such as Ethernet for providing I/Ooperations between applications 110 and SSDs 130. The BMC 121 managesthe motherboard of the chassis and the SSDs present in the chassis via amanagement port (e.g., Intelligent Platform Management Interface (IPMI),NVMe Management Interface (NVMe-MI), Management Component TransportProtocol (MTCP). For example, the BMC 121 can detect insertion, removal,and drive faults of SSDs 130, monitor sensors throughout the chassis,and control a fan speed of the chassis. Both the CPU 120 and the BMC 121are capable of initiating PCIe transactions to the SSDs 130 and othercomponents of the chassis. Typically, the BMC 121 uses a low-cost CPU(e.g., an ARM processor) while the CPU 120 uses a high-performance,high-cost CPU (e.g., an X86 CPU with multicores).

According to one embodiment, the SSDs 130 can push some device-specificinformation to the BMC 121 over a control plane via a PCI bus that isestablished between the motherboard of the chassis and the SSDs 130.Examples of such device-specific information that can be carried overthe control plane include, but are not limited to, discovery informationand field-replaceable unit (FRU) information of the SSDs 130. Inparticular, the device-specific information can be consumed by the BMC121 to identify SSDs 130 that have specific requirements and attributes.This can reduce the burden of the BMC 121 for polling the status of theSSDs 130.

A user or a service manager of the cloud service provider, or anapplication 110 running on a computing node of the datacenter can send aquery to the server 150 to lease computing and/or storage resources fromthe cloud service provider. In response to the query, the server 150communicate with BMC 121 (and other BMCs) in the datacenter to send thedevice-specific information of the SSDs that they manage. According toone embodiment, the SSD information retrieved by the BMC 121 includeattributes of the SSDs 130. Examples of the attributes include, but arenot limited to, a vendor ID (VID), a subsystem vendor ID (SSVID), aserial number (SN), a model number (MN), a capacity, a maximum datatransfer size (MDTS), a number of data units read, a number of dataunits written, host read commands, host write commands, and a controllerbusy time. In addition to the SSD attributes, the BMC 121 can send tothe server 150 additional information of the SSDs 130 such as thecurrent usage and/or availability during a specific time period in whichthe user (or an application) intends to run an application. In oneembodiment, the query of a user may be automatically generated based onan SLA established between the user and the cloud service provider or anapplication 110 that needs additional SSDs 130.

According to one embodiment, the server 150 may be a web server that isconfigured to provide a user interface to a user or a service manager.The communication between the server 150 and the BMC 121 may be via amanagement port. The BMC 121 manages the SSDs 130 present in thechassis, therefore is aware of the status and attributes of all the SSDs130 present in the chassis. According to one embodiment, the BMC 121 cansend the status and attribute information of the SSDs 130 present in thechassis that meet the attributes and are available during the timewindow as specified by the user. Based on the status and attributesinformation received from the BMC 121 and other BMCs in the datacenter,the server 150 can identify a total number of SSDs that can meet therequired status and attributes and are available during the time window.Using the status and attribute information provided by the server 150,the user can decide to enter into a service agreement with the cloudservice provider and commit to use the SSDs for the specified timewindow. Based on the service agreement, the BMC 121 can send a report tothe user that the specified SSDs are available and ready, and the usercan run an application 110 using the storage spaces of the qualifiedSSDs 130 during the specified time window. Upon completion of the lease,the server 150 can notify the user that the service has expired andclean up the SSDs 130 for the next service by sending a command to theBMC 121. Depending on an application specified in the SLA, the BMC 121can optimize and/or initialize the SSDs 130 to prepare the SSDs 130suited for the application.

According to one embodiment, a manager of the cloud service provider ora qualified application running on a computing node in the datacentercan allocate and use the SSDs 130 based on their attributes andavailability. The manager of the cloud service provider may exchange thestatus and attribute information of the SSDs with managers of differentdatacenters to efficiently allocate, assign, and use their SSDs amongthe different datacenters.

According to one embodiment, the BMC 121 may voluntarily send attributeinformation of one or more SSDs to the server 150 when the SSDs becomesavailable. The server 150 can use the attribute information unless thestatus of the SSDs changes and advertise to a requesting party that theSSDs having certain attributes are available to potential users of thecloud service.

FIGS. 2A, 2B, 2C, and 2D show an example flowchart for specifying andoptimizing SSDs present in a chassis using a BMC, according to oneembodiment. According to one embodiment, the BMC can run an optimizer tooptimize the performance of the SSDs. The optimizer is a process that isrun by the BMC and may be implemented as a software or a firmware.Initially, the BMC may not be loaded with the optimizer. In this case,the optimizer may be downloaded externally at request of a user, anapplication, or a manager of the cloud service provider. The BMC loadedwith the optimizer can provide attribute information of the SSDs to arequesting party to optimize the use and conditions of the SSDs.

Referring to FIG. 2A, a manager (e.g., a resource fulfillmentapplication) of the cloud service provider receives a lease order from auser including specified key attributes of SSDs and requests a responsefrom BMCs in a pool. Based on the responses from the BMCs, the managerdetermines the SSDs present in a chassis meeting the specified keyattributes (201). The BMC may already know the type of the SSDs presentin the chassis when the SSDs are inserted into the device ports of thechassis using a sensor. Initially, the BMC may not be equipped with orconfigured to run an optimizer. If the optimizer of the BMC is notenabled or loaded (202), the manager of the cloud service provider candownload the optimizer software or firmware (203). The manager thendetermines whether the chassis is configured to run in ahigh-availability (HA) mode (204). If the chassis is configured as a HAchassis, the manager selects a proper HA driver and enable a redundancyreplication factor of the HA chassis (205). The manager further checksif the HA mode is available for a particular chassis (206). If theselected chassis is a HA chassis but the HA mode is not available, themanager reports an error (250) and determines that the optimizer of theBMC is not enabled (260). If the HA mode is available, the manager loadsthe HA driver selected in step 205 (207) and communicates with a paringpartner (208). In the HA mode, the paring partner can be anothercomputing node in the same chassis or in a different chassis. When apartner fails, the pairing partner can take over the tasks of thepartner. This can minimize or eliminate the system downtime. If thepairing partner is available (209) and a dual path is available for theselected chassis (210), the manager determines the type of the SSDspresent in the chassis. For example, the manager can instruct the BMC toprovide the type of the SSDs. Otherwise, the manager reports a warningand configures to run the chassis in a non-HA mode (211).

Referring to FIG. 2B, the BMC scans SSDs present in the chassis (201).If there is a new SSD to scan, the BMC sends a query for thedevice-specific information to the new SSD and fills the device-specificinformation of the new SSD in a device information table (214). If thereis no more SSD to scan, the BMC sends the collected device-specificinformation to the server (215). This scanning and querying processrepeats until the device-specific information table contains the deviceinformation for all the scanned SSDs present in the chassis.

Referring to FIG. 2C, the BMC configures the SSDs present in the chassisusing the optimizer depending on the type and their attributes. Once theoptimizer is loaded, the BMC is ready to perform the optimizationprocesses as needed. For example, the BMC detects an insertion, aremoval, or a fault of an SSD, and performs the optimizationaccordingly. In one embodiment, the BMC checks if a selected SSD is anNVMe-oF SSD (221) or an NVMe SSD (231). If the selected SSD is anNVMe-oF SSD, the BMC further checks if the selected SSD is from the samevendor and the same model (222). In this case, the vendor may bespecified in a request from a user, an application, or the manager ofthe cloud service provider. If the selected SSD is not from the samevendor, the BMC normalizes the SSD by selecting common parameters (241).In the case of different vendors, the BMC may normalize the SSD bychoosing different SSD(s) from one vender base on common parametersand/or attributes with the SSD(s) from another vendor. After the commonparameters of all the SSDs present in the chassis, the BMC starts to runthe optimizer (243). If the selected SSD is from the same vendor, theBMC selects the NVMe-oF driver (223), loads the selected NVMe-oF driver(224), and selects the SSD (225). If the selected SSD is an NVMe SSD,the BMC selects the NVMe driver (232) and loads the selected NVMe driver(233).

Referring to FIG. 2D, the optimizer of the BMC receives a signature ofan application to be run on the selected SSD (251) as well as the SLAinformation (252). While the application runs (253), the BMC continuesto receive the SLA information until the application stops (260).

FIG. 3 shows example transactions between a BMC and an SSD, according toone embodiment. According to one embodiment, the BMC 310 can run anoptimizer (ON). In the case where the SSD 320 is an NVMe-oF SSD, theoptimizer running on the BMC 310 is supported by the NVMe-oFspecification.

The optimizer sends an IDFY command 351 to the SSD 320. In response tothe IDFY command 351, the SSD 320 prepares and sends the SSD information352 to the BMC 310. After successfully sending the SSD information 352,the SSD 320 sends an IDFY completion entry to the BMC 310. The BMC 310further send a log command to the SSD 320 requesting log information ofthe SSD 320. The SSD 320 sends a log page 355 to the BMC 310. The logpage 355 can include SMART/health information log and a vendor-specificlog page about performance and resource. After successfully sending thelog page, the SSD 320 sends a log completion entry 356.

The optimizer of the BMC can support NVMe-oF SSDs and identify NVMe-oFSSDs that have certain attributes. Based on their attributes, theoptimizer can optimize and normalize different type/size of NVMe-oF SSDspresent in the chassis.

Each NVMe-oF SSD in the chassis can report its own device-specificinformation 350 to the optimizer running on the BMC. The reporting ofthe device-specific information may be periodic or at a request by theBMC. Examples of the device-specific information 350 include, but arenot limited to, a vendor ID (VID), a subsystem vendor ID (SSVID), aserial number (SN), a model number (MN), a capacity, a maximum datatransfer size (MDTS), a number of data units read, a number of dataunits written, host read commands, host write commands, and a controllerbusy time. For example, the NVMe-oF SSD can provide the device-specificinformation 350 to the optimizer via an NVMe Identify (IDFY) commandand/or a CMBQuery service for a quick query.

According to one embodiment, the BMC can send a query to an SSD presentin the chassis requesting its device-specific information 350 at arequest of a requesting party. Based on the device-specific information350 collected for the SSDs present in the chassis, the BMC cancategorize the SSDs into one or more groups based on their attributes.The BMC can provide these attributes to the requesting party before theSSDs are allocated and an application intended to use the SSDs islaunched. The optimizer can collect and analyze the device-specificinformation 350 to provide useful information to the requesting party.For example, the requesting party can make an informed decision as towhether or not the SSDs intended to be used for the application have therequired attributes, configurations, and data profiles.

According to one embodiment, the SSD has a memory buffer that islogically owned, managed, and accessible by the BMC. The BMC maydirectly access the memory buffer of the SSD without involving anyprotocol process.

According to one embodiment, the present disclosure provides a systemand method for providing optimization of a variety of SSDs from multiplevendors. A cloud service provider can provide a pool of SSDs for runningan application based on a customer-defined SLA. Using the SSDinformation collected by the BMC, the cloud service provider canfacilitate a resource-leasing service to a potential user. The user canspecify desired attributes of SSDs and review the attributes and statusof the available SSDs prior to committing to a lease. The BMC can cleanup the SSDs after the current application completes or the current leaseexpires. For example, the BMC can securely erase or tear down the leasedconfigurations and data for the subscription for a new user.

According to one embodiment, the SSDs are reconfigurable based on a needof an application. Some attributes of the SSDs may be changed over aperiod of time after being repeatedly leased and configured fordifferent applications. The BMC can run the optimizer to update theattributes of the SSDs. The host can not only select SSDs that can meeta customer application profile but also reconfigure SSDs that may not becurrently optimized for a specific application. The BMC can reconfigurethe SSDs into an optimal condition ready to run the application beforethe SSDs are assigned to the application.

According to one embodiment, a data storage system includes: a pluralityof data storage devices; a motherboard containing a baseboard managementcontroller (BMC); and a network switch configured to route networktraffic to the plurality of data storage devices. The BMC is configuredto identify a group of data storage devices among the plurality of datastorage devices based on device-specific information received from theplurality of data storage devices and send identifiers of the group ofdata storage devices to a querying party.

The data storage device may be a solid-state drive (SSD) that iscompatible with the NVMe-oF standard, and the network switch may be anEthernet switch, and the plurality of uplink ports and the plurality ofdownlink ports may be Ethernet ports.

Each of the plurality of data storage devices may send thedevice-specific information to the BMC over a PCI bus.

The device-specific information may include discovery information andfield-replaceable unit (FRU) information of the plurality of datastorage devices.

The device-specific information may further include attributes of theplurality of data storage devices including one or more of a vendor ID(VID), a subsystem vendor ID (SSVID), a serial number (SN), a modelnumber (MN), a capacity, a maximum data transfer size (MDTS), a numberof data units read, a number of data units written, host read commands,host write commands, and a controller busy time.

The device-specific information may further include a current usage oravailability of the plurality of data storage devices during a specifictime period.

The BMC may send a query to the plurality of data storage devices inresponse to the querying party, and the plurality of data storagedevices may send the device-specific information to the BMC in responseto the query by the BMC.

The query may be automatically generated based on service levelagreement (SLA).

The query may include requirements of attributes for the data storagedevices.

The BMC may send the group of data storage devices among the pluralityof data storage devices that satisfies the requirements of attributes tothe querying party.

The BMC may be further configured to clean up the group of data storagedevices.

According to another embodiment, a method includes: receivingdevice-specific information from a plurality of data storage devicesincluded in a data storage system using a baseboard managementcontroller (BMC); identifying a group of data storage devices among theplurality of data storage devices based on attributes of the pluralityof data storage devices; and sending identifiers of the group of datastorage devices to a querying party.

The data storage device may be a solid-state drive (SSD) that iscompatible with the NVMe-oF standard, and the network switch may be anEthernet switch, and the plurality of uplink ports and the plurality ofdownlink ports may be Ethernet ports.

Each of the plurality of data storage devices may send thedevice-specific information to the BMC over a PCI bus.

The device-specific information may include discovery information andfield-replaceable unit (FRU) information of the plurality of datastorage devices.

The device-specific information may further include attributes of theplurality of data storage devices including one or more of a vendor ID(VID), a subsystem vendor ID (SSVID), a serial number (SN), a modelnumber (MN), a capacity, a maximum data transfer size (MDTS), a numberof data units read, a number of data units written, host read commands,host write commands, and a controller busy time.

The device-specific information may further include a current usage oravailability of the plurality of data storage devices during a specifictime period.

The BMC may send a query to the plurality of data storage devices inresponse to the querying party, and the plurality of data storagedevices may send the device-specific information to the BMC in responseto the query by the BMC.

The method may further include automatically generating the query basedon service level agreement (SLA).

The query may include requirements of attributes for the data storagedevices.

The BMC may send the group of data storage devices among the pluralityof data storage devices that satisfies the requirements of attributes tothe querying party.

The method may further include: cleaning up the group of data storagedevices using the BMC.

The above example embodiments have been described hereinabove toillustrate various embodiments of implementing a system and method forfine tuning and optimizing NVMe-oF solid-state drives (SSDs). Variousmodifications and departures from the disclosed example embodiments willoccur to those having ordinary skill in the art. The subject matter thatis intended to be within the scope of the invention is set forth in thefollowing claims.

What is claimed is:
 1. A data storage system comprising: a chassisconfigured to removably receive a data storage device; and a controllercoupled to the chassis, wherein the controller sends an identifier of agroup of data storage devices based on device-specific information to aquerying party via a management port of the data storage system.
 2. Thedata storage system of claim 1, wherein the data storage device sendsthe device-specific information to the controller over a control plane.3. The data storage system of claim 2, wherein the control planeincludes a peripheral component interconnect express (PCIe) bus or amanagement Ethernet port.
 4. The data storage system of claim 1, whereinthe data storage device is a solid-state drive (SSD) that is compatiblewith a non-volatile memory express over fabrics (NVMe-oF) standard, andwherein the data storage device further comprises a network switch. 5.The data storage system of claim 1, wherein the device-specificinformation includes discovery information and field-replaceable unit(FRU) information of the data storage device.
 6. The data storage systemof claim 1, wherein the device-specific information further includes anattribute of the data storage device including one or more of a vendorID (VID), a subsystem vendor ID (SSVID), a serial number (SN), a modelnumber (MN), a capacity, a maximum data transfer size (MDTS), a numberof data units read, a number of data units written, host read commands,host write commands, and a controller busy time.
 7. The data storagesystem of claim 1, wherein the device-specific information furtherincludes a current usage or availability of the data storage deviceduring a specific time period.
 8. The data storage system of claim 1,wherein the controller sends a query to the data storage device inresponse to a request received from the querying party, and wherein thedata storage device sends the device-specific information to thecontroller in response to the query by the controller.
 9. The datastorage system of claim 8, wherein the query is automatically generatedbased on a service level agreement (SLA).
 10. The data storage system ofclaim 8, wherein the query includes a requirement of an attribute forthe data storage device, and wherein the controller sends the group ofdata storage devices that satisfies the requirement of the attribute tothe querying party.
 11. A method comprising: identifying, at acontroller coupled to a data storage system, a group of data storagedevices removably attachable to a chassis of the data storage systembased on an attribute of a data storage device, wherein the group ofdata storage system includes a first data storage device; and sending anidentifier of the group of data storage devices from the controller to aquerying party via a management port of the data storage system.
 12. Themethod of claim 11, further comprising receiving, at the controller, thedevice-specific information from the first data storage device over acontrol plane.
 13. The method of claim 12, wherein the control planeincludes a peripheral component interconnect express (PCIe) bus or amanagement Ethernet port.
 14. The method of claim 11, wherein the firstdata storage device is a solid-state drive (SSD) that is compatible witha non-volatile memory express over fabrics (NVMe-oF) standard.
 15. Themethod of claim 11, wherein the device-specific information includesdiscovery information and field-replaceable unit (FRU) information ofthe first data storage device.
 16. The method of claim 11, wherein thedevice-specific information further includes an attribute of the firstdata storage device including one or more of a vendor ID (VID), asubsystem vendor ID (SSVID), a serial number (SN), a model number (MN),a capacity, a maximum data transfer size (MDTS), a number of data unitsread, a number of data units written, host read commands, host writecommands, and a controller busy time.
 17. The method of claim 11,wherein the device-specific information further includes a current usageor availability of the first data storage device during a specific timeperiod.
 18. The method of claim 11, wherein the controller sends a queryto the first data storage device in response to a request received fromthe querying party, and wherein the first data storage device sends thedevice-specific information to the controller in response to the queryby the controller.
 19. The method of claim 18, further comprisingautomatically generating the query based on a service level agreement(SLA).
 20. The method of claim 18, wherein the query includes arequirement of an attribute for the first data storage device, andwherein the controller sends the group of data storage devices thatsatisfies the requirement of the attribute to the querying party.